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Kategorie szczegółowe BISAC

Deep Learning for Multimedia Processing Applications

ISBN-13: 9781032623344 / Twarda / 2024 / 480 str.

Deep Learning for Multimedia Processing Applications  9781032623344 Taylor & Francis Ltd - książkaWidoczna okładka, to zdjęcie poglądowe, a rzeczywista szata graficzna może różnić się od prezentowanej.

Deep Learning for Multimedia Processing Applications

ISBN-13: 9781032623344 / Twarda / 2024 / 480 str.

cena 538,76
(netto: 513,10 VAT:  5%)

Najniższa cena z 30 dni: 503,69
Termin realizacji zamówienia:
ok. 16-18 dni roboczych.

Darmowa dostawa!

This book is a comprehensive guide that explores the revolutionary impact of deep learning techniques in the field of multimedia processing. Volumes Two delves into advanced topics such as convolutional neural networks, recurrent neural networks, and generative adversarial networks, explaining their unique capabilities in multimedia tasks. 

Kategorie:
Technologie
Kategorie BISAC:
Computers > Data Science - Neural Networks
Computers > Interactive & Multimedia
Computers > Computer Science
Wydawca:
Taylor & Francis Ltd
ISBN-13:
9781032623344
Rok wydania:
2024
Ilość stron:
480
Wymiary:
25.4 x 17.8
Oprawa:
Twarda
Dodatkowe informacje:
Bibliografia
Wydanie ilustrowane

1. A Review on Comparative Study of Image-Denoising in Medical Imaging Nasir Ishfaq. 2. Remote Sensing Image Classification: A Comprehensive Review and Applications Uzair Aslam Bhatti, Jingbing Li, Saqib Ali Nawaz, Huang Mengxing, and Raza Muhammad Ahmad. 3. Deep learning framework for Face Detection and Recognition for Dark Faces using VGG19 with Variant of Histogram Equalization Kirti and Gagandeep. 4. A 3D Method for combining Geometric Verification and Volume Reconstruction in a Photo Tourism system Muhammad Sajid Khan and Andrew Ware. 5. Deep Learning Algorithms and Architectures for Multimodal Data Analysis Anwar Ali Sathio, Prof. Dr. Muhammad Malook Rind, and Dr. Abdullah Lakhan. 6. Deep Learning Algorithms - Clustering and Classifications for Multimedia Data Anwar Ali Sathio, Prof. Dr. Muhammad Malook Rind, and Dr. Abdullah Lakhan. 7. A Non-Reference Low-Light Image Enhancement Approach using Deep Convolutional Neural Networks Ziaur Rahman, Muhammad Aamir, Kanza Gulzar, Jameel Ahmed Bhutto, Muhammad Ishfaq, Zaheer Ahmed Dayo, and Khalid Hussain Mohammadani. 8. Human Pose Analysis and Gesture Recognition: Methods and Applications
Muhammad Haroon, Saud Altaf, Kanza Gulzar, and Muhammad Aamir. 9. Human Action Recognition Using ConvLSTM with Adversarial Noise and Compressive-Sensing-Based Dimensionality Reduction Concise and Informative Mohsin Raza Siyal, Mansoor Ebrahim, Dr.Nadeem Qazi, Syed Hasan Adil, and Kamran Raza. 10. Application of Machine Learning to Urban Ecology Mir Muhammad Nizamani, Ghulam Muhae-Ud-Din, Qian Zhang, Muhammad Awais, Muhammad Qayyum, Muhammad Farhan, Muhammad Jabran, and Yong Wang. 11. Application of Machine Learning in Urban Land Use Haili Zhang and Qin Zhou. 12. Application of GIS and Remote Sensing Technology in Ecosystem Services and Biodiversity Conservation Mir Muhammad Nizamani, Qian Zhang, Ghulam Muhae-Ud-Din, Muhammad Awais, Muhammad Qayyum, Muhammad Farhan, Muhammad Jabran, and Yong Wang. 13. From Data Quality to Model Performance: Navigating the Landscape of Deep Learning Model Evaluation Muhammad Akram, Wajid Hassan Moosa, and Najiba. 14. Deep Learning for the Turnover Intention of Industrial Workers: Evidence from Vietnam Nguyen Ngoc Long, Nguyen Ngoc Lam, and Bui Huy Khoi. 15. Deep Learning for Multimedia Analysis Hafiz Gulfam Ahmad Umar. 16. Challenges and Techniques to Improve Deep Detection and Recognition Methods for Text Spotting Anuj Abraham and Shitala Prasad. 17. Leaf Classification and Disease Detection Based on R-CCN Deep Learning Approach Tayyab Rehman, Muhammad Sajid Khan, and Noshina Tariq. 18. Deep Learning for Multimedia Analysis: Applications, Challenges, and Future Directions Dr. Ahmed Mateen Buttar, Muhammad Anwar Shahid, Muhammad Nouman Arshad, and Irfan Ali.

Uzair Aslam Bhatti was born in 1986. He received the Ph.D. degree in information and communication engineering, Hainan University, Haikou, Hainan, in 2019. He completed his Postdoctoral from Nanjing Normal University, Nanjing, China in implementing Clifford algebra algorithms in analysing the geospatial data using artificial intelligence (AI). He is currently working as Associate Professor in School of information and communication engineering in Hainan University. His areas of specialty include AI, machine learning, and image processing. He is serving as guest editor of various journals including Frontier in Plant Science, Frontier in Environmental Science, Computer Materials and Continua, Plos One, IEEE Access etc and has reviewed many IEEE Transactions and Elsevier journals.

Dr. Huang Mengxing is Dean of the School of Information, at Hainan University. He has occupied many roles, such as the leader of the talent team of "Smart Service", the chief scientist of the National Key R&D Program, a member of the Expert Committee of Artificial Intelligence and Blockchain of the Science and Technology Committee of the Ministry of Education, the executive director of the Postgraduate Education Branch of the China Electronics Education Society, and the Computer Professional Teaching Committee of the Ministry of Education, among others. His main research areas include big data and intelligent information processing, multi-source information perception and fusion, artificial intelligence and intelligent services, etc. In recent years, he has published more than 230 academic papers as the first author and corresponding author, has obtained 36 invention patents authorized by the state, and 96 software copyrights; published 4 monographs and translated 2 books. He has won first prize and second prize of Hainan Provincial Science and Technology Progress Award as the first person who completed it; won 2 Hainan Provincial Excellent Teaching Achievement Awards and Excellent Teacher Award. He has presided over and undertaken more than 30 national, provincial, and ministerial-level projects, such as national key research and development plan projects, national science and technology support plans, and National Natural Science Foundation projects.

Jingbing Li, is a Doctor, professor, doctoral supervisor, and the Vice President of Hainan Provincial Invention Association. He has been awarded honorary titles of Leading Talents in Hainan Province, Famous Teaching Teachers in Hainan Province, Outstanding Young and Middle-aged Backbone Teachers in Hainan Province, and Excellent Teachers in Baosteel. He has also won the second prize of Hainan Provincial Science and Technology Progress Award three times (the first completer twice, the second completer once). He has obtained 13 authorized national invention patents, published 5 monographs such as medical image digital watermarking, published more than 80 SCI / EI retrieved academic papers (including 22 SCI retrieved papers) as the first author or corresponding author. He has presided over 2 projects of the National Natural Science Foundation of China, and 5 projects of Hainan Province's key research and development projects and Hainan Province's international scientific and technological cooperation projects.

Sibghat Ullah Bazai completed his undergraduate and graduate studies in Computer Engineering at the Balochistan University of Information Technology, Engineering, and Management Sciences (BUITEMS) in Quetta, Pakistan. He received his Ph.D. (IT) in Cyber Security from Massey University in Auckland, New Zealand in 2020. As part of his research, he is interested in applying cyber security, identifying diseases with deep learning, automating exams with natural language processing, developing local language sentiment datasets, and planning smart cities. Sibghat is a guest editor and reviewer for several journals' special issues in MDPI, Hindawi, CMC, PlosOne, Frontier, and others.

Muhammad Aamir received the Bachelor of Engineering degree in Computer Systems Engineering from Mehran University of Engineering & Technology Jamshoro, Sindh, Pakistan, in 2008, the Master of Engineering degree in Software Engineering from Chongqing University, China, in 2014, and the PhD degree in Computer Science and Technology from Sichuan University, Chengdu, China, in 2019. He is currently an Associate Professor at the Department of Computer, Huanggang Normal University, China. His main research interests include pattern recognition, computer vision, image processing, deep learning, and fractional calculus.



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